Identifying Phenogroups in patients with subclinical diastolic dysfunction using unsupervised statistical learning

Identifying Phenogroups in patients with subclinical diastolic dysfunction using unsupervised statistical learning

Abstract Background Subclinical diastolic dysfunction is a precursor for developing heart failure with preserved ejection fraction (HFpEF); yet not all patients progress to HFpEF. Our objective was to evaluate clinical and echocardiographic variables to identify patients who develop HFpEF. Methods C...

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Bibliographic Details
Main Authors: Yvonne E. Kaptein, Ilya Karagodin, Hongquan Zuo, Yu Lu, Jun Zhang, John S. Kaptein, Jennifer L. Strande
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Cardiovascular Disorders
Subjects:
Diastolic dysfunction
Heart failure with preserved ejection fraction
Unsupervised machine learning
Hierarchical clustering
Clinical studies
Risk factors
Online Access:http://link.springer.com/article/10.1186/s12872-020-01620-z

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http://link.springer.com/article/10.1186/s12872-020-01620-z

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